Triple
T12073191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Confession of Brother Haluin |
E287475
|
entity |
| Predicate | featuresDetectiveType |
P63938
|
FINISHED |
| Object | monk-detective |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: monk-detective | Statement: [The Confession of Brother Haluin, featuresDetectiveType, monk-detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDetectiveType Context triple: [The Confession of Brother Haluin, featuresDetectiveType, monk-detective]
-
A.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
B.
featuresDetectiveDuo
Indicates that the subject involves or centers around a pair of detectives working together as a team.
-
C.
hasFictionalDetective
chosen
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
D.
detectorType
Indicates the specific kind or category of detector associated with an entity or measurement.
-
E.
fictionalDetective
Indicates that the subject is a detective character who exists only in fiction rather than in real life.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.